1. Field of the Invention
The system shown in FIG. 1 is integrated with a milking stand 1 for milking individual cows one by one. The milking stand further includes a milking device with four suction cups 2-5, to be connected to a cow for withdrawing milk from that cow. Milk channels 5xe2x80x2-8xe2x80x2 are connected at their upstream ends to suctions cups 2-and at their downstream ends to the conductive sensors 9-12. The conductivity sensors 9-12 are part of a conductivity measurement unit 13. In the conductivity measurement unit 13, the milk channels 5xe2x80x2-8xe2x80x2 merge downstream from the conductivity sensors 9-12 into a single milk channel 14 passing through a flow meter 15 for measuring the milk yield.
2. Description of the Prior Art
In xe2x80x98Modelling Daily Milk Yield in Holstein cows Using Time-series Analysisxe2x80x99 by Deluyker et al. in the Journal of Dairy Science, 73:539-548, an experimental method for automatically monitoring the physical condition of a herd of livestock is described which includes the steps of: measuring a value of a property at regular intervals from each individual, identified animal, storing measurement data in accordance with the measured values of the measured property for each individual, identified animal, determining a prediction for a subsequent measured value of that property for the respective individual, identified animal from the stored measurement data regarding that individual, identified animal, and generating an attention signal in response to an error between the value of the measured property and the prediction for that value above a predetermined level.
In this experimental method, the measured property was the milk yield.
For carrying out the measurements an automated cow identification and milk yield recording system was used.
After the observation period, a time-series model was formulated for predicting the milk yield of each milking or set of three successive milkinq with sets of parameters each generally applicable in a particular period of time during a lactation for either heifers or multiparous cows.
A disadvantage of this described method is, that it is cumbersome in that for each cow the appropriate set of parameters has to be selected. This also forms a potential source of errors. Furthermore, it is unlikely that the determined parameters will also apply to herds of cows of different races or even herds of other animals (e.g. goats), herds kept in other climates or fed with different types of feed.
It is an object to the invention to provide a reliable system and a method for automated monitoring the physical condition of a herd of animals which is more universally applicable than the model proposed by Deluyker et al.
According to the invention, this object is achieved by providing a system as described in claim 1 and a method as described in claim 5.
Since, in the method according to the invention and, in operation, in the system according to the invention, during a lactation, error data are stored in accordance with predicted values and corresponding measured values for each individual, identified animal, and a confidence interval for a prediction is determined for each individual, identified animal, and for that same lactation, from the error data characterizing the distribution of the errors, the method automatically assesses the significance of an error between a prediction and a measured value for each animal individually from data collected during the respective lactation. The confidence interval can be determined automatically for each individual measurement and each individual animal, so there is no need to input different selected confidence intervals for different periods of the lactation, for different categories of animals and for different measured properties. Furthermore, the need for separate research to obtain such confidence intervals is obviated.
Since the significance of errors is assessed for each animal individually, any adverse effect of unreliable predictions due to errors in the choice of the parameters of the time-series model, if applicable, is reduced. For each individual animal and each monitored variable, the width of the confidence interval is automatically adjusted on-line to the empirically found accuracy of fit of the time-series model and can be signalled separately to indicate the reliability of the predictions.
The measured property can for example be one of the following properties: milk yield, milk temperature, milk conductivity, animal activity and intake of at least one type of feed.
The method according to the invention has a prophylactic and accordingly productivity-increasing effect in that it allows an earlier and more reliable identification of individual animals likely to be ill. Firstly, the sooner animals to be checked by a veterinarian can be identified, the better the chances of recovery and the avoidance of adverse effects on the animal are and the better the chances are that further spread of a contagious disease through the herd can be avoided. Secondly, animals having a bad physical condition are accordingly more prone to catching diseases or, if already ill, further diseases. The sooner such animals are identified, the sooner action can be taken to improve the physical condition of such animals and to avoid that the identified animal catches a disease or a further disease
A productivity-increasing effect can also achieved by earlier oestrus detection, which allows shortening the calving interval.
According to one particular mode of carrying out the method according to the invention, the error data are used to characterize the mutual dependence between errors in the predictions of the conductivities of milk obtained from different teats (quarters if the animals are cows). The data regarding this dependence are subsequently used for assessing the significance of errors in the prediction of the conductivity of milk obtained from any one of the teats.
According to a further particular mode of carrying out the invention, the error data collected during a lactation are also used to estimate the parameters of the time-series model underlying the predictions of the measured values during that same lactation for each animal individually. Thus, for each individual animal, the time-series model is automatically tailored to an optimal fit to the characteristics of the variations in time of the respective property of that individual animal as the lactation progresses.
Particular features and advantages of the present invention appear from the dependent claims and the detailed description set forth below in which reference is made to the drawings.